Despite innovations leading to more robust and efficient computing systems and software, the role of mainframe computing remains vital to many businesses and organizations. In most cases, mainframe computing systems that are in use today were originally implemented prior to the computing innovations of the 1980's and 1990's. However, many businesses and organizations have concluded that it would be too expensive and too intrusive to day-to-day business operations to upgrade their major systems to newer technologies. Therefore, to enable continued expansion of computing infrastructures to take advantage of newer technologies, much effort has been devoted to developing ways to integrate older mainframe technologies with newer server and component based technologies. For instance, COBOL is one of the oldest programming languages. It is a legacy language in use by many organizations. Its name is an acronym for Common Business-Oriented Language, defining its primary domain in business, finance, and administrative systems for companies and governments.
Traditionally, the mainframe batch application programs access data (static or dynamic) through input datasets. These processing routines are typically opened, read, and closed to access and transfer data from a database. Stated another way, the traditional mainframe application developers access data for use in a program via the file input/output (I/O). Application developers have not attempted to efficiently access static data via application data loaded into an application program.
The aforementioned traditional process involves high consumption of I/O processing and high CPU cost for accessing the data through the datasets. Therefore, a need exists for a system and method for increasing computing efficiency and speed within a mainframe environment.